Mathematical Finance vs Other Programs or Options

[CSTraderDan]

Hi All,

I'm currently in a MS Computer Science program (highly ranked) in the US and would like to move to Chicago, afterwards, to work in something closely related to machine learning and high-performance computing. Finance (especially trading) is an area that has interested me for a long time, but I would also like to keep my options open. My undergrad was math (took a bunch of grad statistics courses) and my CS specialization is ML (but I'm also studying HPC and taking systems courses in OS, Architecture, Compilers, etc.). My prior work experience is unrelated to finance, and I have read perhaps 50-100 books on a mix of trading strategies, market structure, fundamental analysis, and numerous other finance/investing topics. I have limited knowledge of stochastic calculus (but know stochastic processes from a statistics perspective).

The options I'm considering:

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-- MSFM Program at University of Chicago. I would probably do this part-time while working. It seems expensive. I'm not sure if this would be overly specialized for roles that would make limited use of my CS/ML background? Also, almost all of the computing courses seem remedial. Perhaps the alumni network would be useful?​

-- There's some Statistics programs that I'm looking at that could be done part-time. They're more broad in the sense that I could take courses focused on big data technologies, optimization, simulation, Bayesian statistics, etc.​

-- Try to complete a research project with one of the professors in my current program (there's some who are experts in certain areas of finance as it relates to computing)​

-- Do more independent study and just apply for jobs​

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What do you guys suggest?​

 

[Onegin]

Chicago has a lot of prop trading shops - Chicago Trading Company, Akuna, Optiver, IMC. If you've done a lot of brain teasers and leetcode, you'd have a good shot if you are from a top program. There's another thread on here about whether the MFE is actually worth it - and some good insights there.